Environment management apparatus for inside of machine, electronic machine, image forming apparatus, environment management method for inside of machine, and non-transitory computer readable medium

ABSTRACT

An environment management apparatus for inside of a machine includes an estimator and a generator. The estimator estimates an environment state in the machine in a case of executing a process under a predetermined control condition, from process execution data for instructing execution of the process. The generator generates, for the environment state estimated by the estimator, a time-series scheme for environment control during the execution of the process from a calculation result obtained by calculating a control condition which maintains the environment state to be less than or equal to a predetermined target value.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2015-243262 filed Dec. 14, 2015.

BACKGROUND Technical Field

The present invention relates to an environment management apparatus forinside of a machine, an electronic machine, an image forming apparatus,an environment management method for inside of a machine, and anon-transitory computer readable medium.

SUMMARY

According to an aspect of the invention, an environment managementapparatus for inside of a machine includes an estimator and a generator.The estimator estimates an environment state in the machine in a case ofexecuting a process under a predetermined control condition, fromprocess execution data for instructing execution of the process. Thegenerator generates, for the environment state estimated by theestimator, a time-series scheme for environment control during theexecution of the process from a calculation result obtained bycalculating a control condition which maintains the environment state tobe less than or equal to a predetermined target value.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention will be described indetail based on the following figures, wherein:

FIG. 1 is a block diagram illustrating an electrical configuration of anin-apparatus environment management apparatus according to an exemplaryembodiment;

FIG. 2 is a block diagram illustrating a functional configuration of thein-apparatus environment management apparatus according to the exemplaryembodiment;

FIG. 3 is a flowchart illustrating a flow of a program for anin-apparatus environment management process according to the exemplaryembodiment;

FIG. 4 is a schematic diagram illustrating an example of a setting stateof each node of a Bayesian network at a time of estimating anenvironment state in the in-apparatus environment management apparatusaccording to the exemplary embodiment;

FIG. 5 is a schematic diagram illustrating an example of the settingstate of each node of the Bayesian network at a time of estimatingenvironment control conditions in the in-apparatus environmentmanagement apparatus according to the exemplary embodiment;

FIG. 6 is a table illustrating an example of an estimation result for aprobability value for each combination of a fan air volume and anopening state in the in-apparatus environment management apparatusaccording to the exemplary embodiment;

FIG. 7A is a table illustrating an example of a relationship among anexecution time, a rise in temperature, and a degree of pollution foreach combination of the fan air volume and the opening state in thein-apparatus environment management apparatus according to the exemplaryembodiment;

FIG. 7B is a table illustrating another example of a relationship amongan execution time, a rise in temperature, and a degree of pollution foreach combination of the fan air volume and the opening state in thein-apparatus environment management apparatus according to the exemplaryembodiment;

FIG. 8 is a graph illustrating an example of a relationship between anelapsed time and a rise in temperature in the in-apparatus environmentmanagement apparatus according to the exemplary embodiment; and

FIG. 9 is a graph illustrating an example of a relationship between anelapsed time and a degree of pollution in the in-apparatus environmentmanagement apparatus according to the exemplary embodiment.

DETAILED DESCRIPTION

Hereinafter, an in-apparatus environment management apparatus accordingto the present exemplary embodiment will be described with reference tothe appended drawings. In the present exemplary embodiment, thein-apparatus environment management apparatus will be described as beingapplied to an image forming apparatus. Herein, the inside of a casing ofthe image forming apparatus may be referred to as “in-apparatus,”“inside of a machine”, or “inside of the image forming apparatus,” andthe environment inside of the casing of the image forming apparatus maybe referred to as “in-apparatus environment,” “environment in amachine,” or “environment in the image forming apparatus.”

As illustrated in FIG. 1, an image forming apparatus 10 according to thepresent exemplary embodiment includes a controller 30 that controls theentirety of the apparatus. Various types of functions are realized bycontrol of the image forming apparatus 10 using the controller 30. Thecontroller 30 includes a central processing unit (CPU) 32 that executesvarious types of processes including an in-apparatus environmentmanagement process, described later, and a read-only memory (ROM) 34that stores a program used in processing of the CPU 32 and various typesof information. In addition, the controller 30 includes a random accessmemory (RAM) 36 that, as a work area for the CPU 32, temporarily storesvarious types of data and a non-volatile memory 38 that stores varioustypes of information used in processing of the CPU 32. Furthermore, thecontroller 30 includes an I/O interface 40 that performs input andoutput of data with respect to an external apparatus connected to theimage forming apparatus 10.

The I/O interface 40 is connected with an image forming unit 12 thatincludes developing rolls and forms an image on paper. If the imageforming unit 12 obtains image forming data for instructing execution ofimage formation from the external apparatus or the like, the imageforming unit 12 forms an image on paper based on the image forming dataobtained. The image forming data is an example of process execution datafor instructing execution of a process and includes image data of theformed image and image forming condition data that indicates imageforming conditions. In the present exemplary embodiment, the imageforming condition data includes the number of images formed, theproportion of a color image in the formed image, an image density, andthe like as the image forming conditions. The image forming unit 12outputs the obtained image forming data to an image forming dataobtaining unit 14, described later, to notify the image forming dataobtaining unit 14 that image formation will be executed.

An Image forming process that is executed by the image forming unit 12if instructed to perform image formation will be described. The imageforming unit 12 includes photosensitive bodies which are image carriersfor respective colors, and these photosensitive bodies have surfacesthereof charged by application of a charging bias. The image formingunit 12 obtains image data for each color, forms electrostatic latentimages on the photosensitive bodies by exposing the charged surfaces ofthe photosensitive bodies to exposure light that is modulated based onthe image data for each color, and causes developers (toners) of eachcolor to be held on the photosensitive bodies. The image forming unit 12includes developing rolls for each color. Application of a developingbias to the developing rolls develops the electrostatic latent images onthe photosensitive bodies with the toners of each color and forms tonerimages on the photosensitive bodies. The image forming unit 12 transfersthe toner images of each color formed on the photosensitive bodies to anintermediate transfer belt and transfers and fixes the toner images,which are transferred onto the intermediate transfer belt, to paper,thereby forming an image on the paper.

The I/O interface 40 is connected with an operating unit 42 that isoperated by a user, a display unit 44 that displays various types ofinformation, and a communication unit 46 that communicates with theexternal apparatus. In addition, the I/O interface 40 is connected witha fan 48, an opening changing unit 50, and a path changing unit 52.

The fan 48, under control of the CPU 32, blows air in the apparatus andcauses the air to circulate in the apparatus to decrease thein-apparatus temperature or blows air to the developing rolls todecrease the temperature of the developing rolls. At this point, the fan48 changes the volume of blown air under control of the CPU 32. In thepresent exemplary embodiment, the fan 48 changes the volume of air toone of three-level discrete values of LOW, MID, and HIGH.

The opening changing unit 50 changes the opening state of openingportions that are provided so as to penetrate the casing, under controlof the CPU 32. In the present exemplary embodiment, multiple openingportions are disposed in the casing of the image forming apparatus, andthe opening changing unit 50 changes the opening state of each openingportion to one of an opened state and a closed state. However, themethod for changing the opening state is not limited thereto. Theopening area of each opening portion may be changed by covering at leasta part of each opening portion with a lid portion, thereby placing eachopening portion into a half-opened state. In the present exemplaryembodiment, the opening changing unit 50 changes the opening state ofthe opening portions in such a manner that the total opening area ofeach opening portion is set to one of three-level discrete values ofLOW, MID, and HIGH.

The path changing unit 52 changes a path along which the in-apparatusair flows, under control of the CPU 32. Examples of a method forchanging the path include a method that changes the path of the air flowby changing the position, direction, and the like of a guide whichguides the air. In the present exemplary embodiment, the path changingunit 52 changes the path of the air flow in such a manner that the pathof the air flow is set to one of three paths of a path A, a path B, anda path C.

Hereinafter, the opening state of the opening portions will be simplyreferred to as “opening state”, and the path of the air flow will besimply referred to as “path”.

The I/O interface 40 is connected with a temperature sensor 54 thatmeasures the in-apparatus temperature and a humidity sensor 56 thatmeasures in-apparatus humidity. The temperature sensor 54 measures thein-apparatus temperature in response to an instruction from the CPU 32and notifies the CPU 32 of the measured in-apparatus temperature. Thehumidity sensor 56 measures the in-apparatus humidity in response to aninstruction from the CPU 32 and notifies the CPU 32 of the measuredin-apparatus humidity.

The I/O interface 40 is connected with a pollution sensor 58 thatmeasures the degree of in-apparatus pollution and a noise sensor 60 thatmeasures the degree of in-apparatus noise.

In-apparatus pollution in the present exemplary embodiment is generallypollution that is generated by toners scattered in the casing or bytoners settling on components disposed in the casing. The pollutionsensor 58 is exemplified by a particle sensor, an electrical sensor, ameasurer that measures the weight of settling toners, and the like. Thepollution sensor 58 measures the degree of in-apparatus pollution inresponse to an instruction from the CPU 32 and notifies the CPU 32 ofthe measured degree of in-apparatus pollution.

Noise in the present exemplary embodiment is generally noise from thefan 48 and noise from transport of paper. Noise from the fan 48 ishighly correlated with the volume of air from the fan 48, and noise fromtransport of paper is highly correlated with the opening state. Thenoise sensor 60 is exemplified by a microphone, a capacitor microphone,an acoustic pressure sensor, an acoustic particle velocity sensor, andthe like. The noise sensor 60 measures the degree of noise in responseto an instruction from the CPU 32 and notifies the CPU 32 of themeasured degree of noise.

The image forming apparatus 10 to which the in-apparatus environmentmanagement apparatus according to the present exemplary embodiment isapplied estimates the in-apparatus environment while executing imageformation and controls the in-apparatus environment based on anestimation result, thereby stabilizing the in-apparatus environment.

That is, the image forming apparatus 10 estimates the state of thein-apparatus environment in a case of executing a process underpredetermined in-apparatus control conditions (environment controlconditions), based on the image forming data which is the processexecution data for instructing execution of the process. The imageforming apparatus 10 generates, the estimated environment state, atime-series scheme (hereinafter, referred to as “time division scheme”)for environment control during execution of a process from a calculationresult obtained by calculating environment control conditions thatmaintain the environment state to be less than or equal to predeterminedtarget values. Then, the image forming apparatus 10 controls thein-apparatus environment control conditions based on the generated timedivision scheme.

The present exemplary embodiment will be described in a case ofexecuting a process with setting of the environment control conditionsthat targets the volume of air from the fan 48, the opening state, andthe path. However, the targets of the environment control conditions arenot limited thereto. A process may be executed under environment controlconditions that are related to two of the volume of air from the fan 48,the opening state, and the path. In addition, the present exemplaryembodiment will be described in a case where environment control targetsthe environment state including the temperature of the developing rolls,the degree of in-apparatus pollution, and the degree of noise. However,the targets of environment state control are not limited thereto.Environment state control may target at least two of the temperature ofthe developing rolls, the degree of in-apparatus pollution, and thedegree of noise. Alternatively, environment state control may target atleast two of the temperature of the developing rolls, the degree ofin-apparatus pollution, the degree of noise, the in-apparatustemperature, the in-apparatus humidity, and the degree of in-apparatusodor.

However, there is a so-called trade-off between the environment controlconditions such that changing a part of the environment controlconditions improves a part of the environment state but degrades theother part of the environment state. For example, if the volume of airfrom the fan 48 is increased, the temperature of the developing rolls isdecreased, while the degree of pollution and the degree of noise areincreased. If the opening area of the opening portions is decreased, thedegree of pollution and the degree of noise are decreased, while thetemperature of the developing rolls is increased.

In the present exemplary embodiment, therefore, the in-apparatusenvironment is stabilized by appropriately changing the environmentcontrol conditions in such a manner that the environment state satisfiesthe target values, as described above. Specifically, a probabilisticinference model is built from an interrelationship between eachenvironment state by using a causal network, probability values of adiscrete state of each environment state are estimated by using theprobabilistic inference model built, and target values are set for eachenvironment state. In addition, probability values of a discrete stateof each environment control condition with respect to the target valuesof each environment state are inferred by using the same probabilisticinference model, and the environment control conditions that satisfy thetarget values of each environment state are estimated based on theinferred probability values. Then, in the present exemplary embodiment,the time division scheme for the environment control conditions duringimage formation is generated based on the estimated environment controlconditions, and the in-apparatus environment is controlled based on thegenerated time division scheme.

The present exemplary embodiment is described in a case of using aBayesian network as the probabilistic inference model using a causalnetwork. In the Bayesian network, causal characteristics are representedas a network (weighted graph) using a directed graph (link usingarrows), and performing probabilistic inference on the network allowsthe likelihood of occurrence or the possibility of a complex anduncertain event to be predicted. In the Bayesian network, information asto an interrelationship between each node is accumulated in advance, andcalculating probability values of occurrence for each path based on theaccumulated information as to the interrelationship between each nodeallows a probability value of occurrence of a causal relationshipaccompanying a complex path to be quantitatively represented.

Next, a functional configuration of the image forming apparatus 10 towhich the in-apparatus environment management apparatus according to thepresent exemplary embodiment is applied will be described in detail.

As illustrated in FIG. 2, the image forming apparatus 10 according tothe present exemplary embodiment includes the image forming dataobtaining unit 14, a target value determination unit 16, an environmentdata obtaining unit 18, an environment state estimation unit 20, a timedivision scheme generation unit 22, and an environment control section24. The image forming data obtaining unit 14, the target valuedetermination unit 16, the environment data obtaining unit 18, theenvironment state estimation unit 20, the time division schemegeneration unit 22, and the environment control section 24 are realizedunder control of the controller 30 (CPU 32).

The image forming data obtaining unit 14 obtains the image forming datafrom the image forming unit 12 when the image forming unit 12 executesimage formation. The image forming data obtaining unit 14 outputs theobtained image forming data to the target value determination unit 16and the environment state estimation unit 20.

The target value determination unit 16 obtains the image forming datafrom the image forming unit 12. The target value determination unit 16determines target values for each of the temperature of the developingrolls, the degree of in-apparatus pollution, and the degree of noisethat have to be maintained from the start of image formation based onthe image forming data until the end thereof. The target valuedetermination unit 16 outputs the determined target values to theenvironment state estimation unit 20 and the time division schemegeneration unit 22.

The environment data obtaining unit 18 obtains the in-apparatustemperature from the temperature sensor 54 and obtains the in-apparatushumidity from the humidity sensor 56 as environment data. Theenvironment data obtaining unit 18 outputs the obtained in-apparatustemperature and the in-apparatus humidity to the environment stateestimation unit 20.

The environment state estimation unit 20 obtains the image forming datafrom the image forming data obtaining unit 14. The environment stateestimation unit 20 estimates the environment state in the apparatus in acase of executing image formation based on the image forming data underpredetermined environment control conditions. The present exemplaryembodiment assumes that the predetermined environment control conditionsinclude the volume of air from the fan 48 being set to a predeterminedvalue, the opening state changed by the opening changing unit 50 beingset to a predetermined opening state, and the path changed by the pathchanging unit 52 being set to a predetermined path. In addition, in thepresent exemplary embodiment, the temperature of the developing rolls,the degree of in-apparatus pollution, and the degree of noise in a caseof executing image formation based on the image forming data under thepredetermined environment control conditions are estimated as theenvironment state. The environment state estimation unit 20 outputs theestimated environment state to the time division scheme generation unit22.

The time division scheme generation unit 22 obtains the environmentstate estimated by the environment state estimation unit 20 and thetarget values determined by the target value determination unit 16. Thetime division scheme generation unit 22 estimates the environmentcontrol conditions that are used to maintain the obtained environmentstate less than or equal to the target values. The time division schemegeneration unit 22 generates the time division scheme that is used tochange the environment control conditions during image formation, basedon the environment control conditions used to maintain the environmentstate less than or equal to the target values. The time division schemegeneration unit 22 outputs the generated time division scheme to theenvironment control section 24.

The environment control section 24 obtains the time division scheme fromthe time division scheme generation unit 22. The environment controlsection 24 controls changing of the volume of air from the fan 48,changing of the opening state by the opening changing unit 50, andchanging of the path by the path changing unit 52 in a time-seriesmanner in synchronization with image formation executed by the imageforming unit 12 based on the obtained time division scheme.

Next, a flow of the in-apparatus environment management process executedby the image forming apparatus 10 according to the present exemplaryembodiment will be described with reference to the flowchart illustratedin FIG. 3.

In the present exemplary embodiment, a program for the in-apparatusenvironment management process is stored in advance in the non-volatilememory 38 but is not limited thereto. For example, the program for thein-apparatus environment management process may be received from theexternal apparatus through the communication unit 46 and then executed.Alternatively, the program for the in-apparatus environment managementprocess may be recorded on a recording medium such as a CD-ROM and readthrough the I/O interface 40 such as a CD-ROM drive to execute thein-apparatus environment management process.

In the present exemplary embodiment, the program for the in-apparatusenvironment management process is executed each time a constant periodof time (for example, 0.1 seconds) elapses while the image formingapparatus 10 operates. However, the timings at which the program for thein-apparatus environment management process is executed are not limitedthereto. The program may be executed at a timing when an instruction toexecute the program is input from the operating unit 42.

In Step S101, the image forming data obtaining unit 14 determineswhether or not there is an instruction to perform image formation usingthe image forming unit 12. In the present exemplary embodiment, asdescribed above, in a case where the image forming unit 12 executesimage formation based on the image forming data, the image forming unit12 notifies the image forming data obtaining unit 14 that imageformation will be executed, by transmitting the image forming data tothe image forming data obtaining unit 14. Accordingly, if the imageforming data obtaining unit 14 receives the image forming data from theimage forming unit 12, the image forming data obtaining unit 14determines that there is an instruction to perform image formation. Ifit is determined that there is an instruction to perform image formationin Step S101 (Y in S101), the process transitions to Step S103. If it isdetermines that there is no instruction to perform image formation (N inS101), execution of the program for the in-apparatus environmentmanagement process is ended.

In Step S103, the image forming data obtaining unit 14 calculates fromthe obtained image forming data necessary time that is required forimage formation based on the image forming data. The necessary time iscalculated by using the image forming conditions which are the number ofimages formed, the ratio of color/black-and-white, the image density,and the like. For example, the necessary time is calculated by using acalculation formula that is obtained in advance by experiment, with eachof the number of images formed, the ratio of color/black-and-white, andthe image density as variables.

In Step S105, the environment data obtaining unit 18 obtains theenvironment data. In the present exemplary embodiment, the environmentdata obtaining unit 18 obtains the in-apparatus temperature from thetemperature sensor 54 and obtains the in-apparatus humidity from thehumidity sensor 56 as the environment data. In addition, in the presentexemplary embodiment, the environment data obtaining unit 18 representsthe obtained in-apparatus temperature as one of three-level discretelevels of LOW, MID, and HIGH. In addition, the environment dataobtaining unit 18 represents the obtained in-apparatus humidity as oneof three-level discrete levels of LOW, MID, and HIGH.

In Step S107, the environment state estimation unit 20 sets each of theenvironment control conditions to predetermined values. In the presentexemplary embodiment, the environment state estimation unit 20 sets eachof the volume of air from the fan 48, the opening state, and the path topredetermined values. The present exemplary embodiment will be describedin a case where, for example, the volume of air from the fan 48 is setto, for example, MID, the opening state changed by the opening changingunit 50 is set to, for example, MID, and the path changed by the pathchanging unit 52 is set to the path B.

In Step S109, the environment state estimation unit 20 estimates theenvironment state in a case of performing image formation based on theimage forming data. The environment state estimation unit 20, forexample, uses a Bayesian network 80 illustrated in FIG. 4 to estimatethe environment state in a case of performing image formation based onthe image forming data.

As illustrated in FIG. 4, the Bayesian network 80 is connected with ninenodes 82A to 82I as described below. That is, the Bayesian network 80 isconnected with the node 82A in which the volume of air from the fan 48is set, the node 82B in which the opening state is set, and the node 82Cin which the path is set. In addition, the Bayesian network 80 isconnected with the node 82D in which the in-apparatus humidity is set,the node 82E in which the in-apparatus temperature is set, and the node82F in which image forming conditions are set. In addition, the Bayesiannetwork 80 is connected with the node 82G in which the degree of noiseis set, the node 82H in which the temperature of the developing rolls isset, and the node 82I in which the degree of pollution in the apparatusis set.

The environment state estimation unit 20 sets “MID” in the node 82A inwhich the volume of air from the fan 48 is set, “MID” in the node 82B inwhich the opening state is set, and “path B” in the node 82C in whichthe path is set, in the Bayesian network 80. In addition, in theBayesian network 80, the environment state estimation unit 20 sets “LOW”in the node 82D in which the in-apparatus humidity is set and “MID” inthe node 82E in which the in-apparatus temperature is set, based on theenvironment data obtained in Step S105. In addition, the environmentstate estimation unit 20 sets the image forming conditions included inthe image forming data in the node 82F in which image forming conditionsare set.

Meanwhile, in the present exemplary embodiment, the environment stateestimation unit 20 does not set values in the node 82G in which thedegree of noise is set, in the node 82H in which the temperature of thedeveloping rolls is set, and in the node 82I in which the degree ofin-apparatus pollution is set.

As described above, probability tables that represent probability valuesof occurrence for each path are created in the Bayesian network 80 basedon information as to an interrelationship among the nodes 82A to 82Ithat is accumulated in advance. The environment state estimation unit 20estimates probability values that will be used as the values of each ofthe nodes 82G to 82I, which are not set with values, based on the valuesset in each of the nodes 82A to 82F, which are set with values, usingthe Bayesian network 80.

As illustrated in FIG. 4, it is assumed that the volume of air from thefan 48 is set to “MID”, the opening state is set to “MID”, the path isset to “path B”, the in-apparatus humidity is set to “LOW”, and thein-apparatus temperature is set to “MID”. In this case, for example, theprobability values that the degree of noise is “LOW”, “MID”, and “HIGH”are respectively 10%, 80%, and 10%. The probability values that thedegree of temperature of the developing rolls is “LOW”, “MID”, and“HIGH” are respectively 25%, 73%, and 2%. The probability values thatthe degree of in-apparatus pollution is “LOW”, “MID”, and “HIGH” arerespectively 15%, 80%, and 5%.

In Step S111, the target value determination unit 16 sets target valuesfor each environment state based on the temperature of the developingrolls, the degree of in-apparatus pollution, and the degree of noiseestimated by using the Bayesian network 80. In the present exemplaryembodiment, the estimated temperature of the developing rolls, thedegree of in-apparatus pollution, and the degree of noise are displayedin the display unit 44 along with the target values of each environmentstate, and the user is allowed to input or correct the target values ofeach environment state. Then, the target value determination unit 16sets the input or corrected target values as the target values of eachenvironment state.

In Step S113, the time division scheme generation unit 22 estimates theenvironment control conditions that satisfy the set target values of theenvironment state. That is, in the Bayesian network 80, the timedivision scheme generation unit 22, for example, sets “MID” in the node82G in which the degree of noise is set and “LOW” in the node 82H inwhich the temperature of the developing rolls is set. In addition, thetime division scheme generation unit 22 sets “MID” in the node 82I inwhich the degree of in-apparatus pollution is set. The time divisionscheme generation unit 22 sets “MID” in the node 82D of the Bayesiannetwork 80 in which the in-apparatus humidity is set and “HIGH” in thenode 82E of the Bayesian network 80 in which the in-apparatustemperature is set, as the in-apparatus humidity and the in-apparatustemperature predicted in a case of executing image formation. In thepresent exemplary embodiment, the in-apparatus temperature and thein-apparatus humidity after image formation are set by predicting thateach of the in-apparatus temperature and the in-apparatus humidity isincreased by one level due to image formation. That is, the in-apparatushumidity that is “LOW” in the environment data obtained in Step S105 isset to “MID”, and the in-apparatus temperature that is “MID” in theenvironment data obtained in Step S105 is set to “HIGH”. The timedivision scheme generation unit 22 sets the image forming conditionsincluded in the image forming data in the node 82F in which imageforming conditions are set.

Meanwhile, in the present exemplary embodiment, the time division schemegeneration unit 22 does not set values in the node 82A in which thevolume of air from the fan 48 is set and in the node 82B in which theopening state is set. In addition, in the present exemplary embodiment,the path that is changed by the path changing unit 52 is assumed to befixed to “path B”. Accordingly, the environment state estimation unit 20sets “path B” in the node 82C in which the path is set.

The time division scheme generation unit 22 estimates probability valuesthat will be used as the values of each of the nodes 82A and 82B, whichare not set with values, based on the values set in each of the nodes82C to 82I, which are set with values, using the Bayesian network 80.

As illustrated in FIG. 5, it is assumed that the degree of noise is setto “MID”, the temperature of the developing rolls is set to “LOW”, thedegree of in-apparatus pollution is set to “MID”, the in-apparatushumidity is set to “MID”, the in-apparatus temperature is set to “HIGH”,and the path is set to “path B”. In this case, for example, theprobability values that the volume of air from the fan 48 is “LOW”,“MID”, and “HIGH” are respectively 1.92%, 60.2%, and 37.9%. Theprobability values that the opening state is “LOW”, “MID”, and “HIGH”are respectively 16.7%, 37.3%, and 46%.

FIG. 6 illustrates an example of an estimation result that is obtainedby calculating probability values corresponding to each combination ofthe environment control conditions, the volume of air from the fan 48and the opening state changed by the opening changing unit 50. In theexample illustrated in FIG. 6, states where the volume of air from thefan 48 is LOW, MID, and HIGH are respectively denoted by A1, A2, and A3,and states where the opening state of the opening changing unit 50 isLOW, MID, and HIGH are respectively denoted by B1, B2, and B3.

In the example illustrated in FIG. 6, the probability value is 0.003206in a case where, for example, the state of the volume of air is A1 andthe state of changing by the opening changing unit 50 is B1, and theprobability value is 0.007162 in a case where, for example, the state ofthe volume of air is A1 and the state of changing by the openingchanging unit 50 is B2.

In Step S115, the time division scheme generation unit 22 normalizes theprobability values corresponding to each combination of the environmentcontrol conditions by the necessary time required for image formation.Specifically, the time division scheme generation unit 22 calculates anintegrated value R of a probability value r corresponding to eachcombination of the environment control conditions. In addition, the timedivision scheme generation unit 22 calculates necessary time T that isrequired for image formation based on the image forming data, from theimage forming data obtained by the image forming data obtaining unit 14.Then, the time division scheme generation unit 22 calculates anexecution time t for each combination of the environment controlconditions using the following Equation (1).

$\begin{matrix}{t = {\frac{r}{R} \times T}} & (1)\end{matrix}$

The example illustrated in FIG. 6 illustrates the execution time t foreach combination of the environment control conditions in a case ofsetting the necessary time to 30 minutes.

In Step S117, the time division scheme generation unit 22 generates thetime division scheme for the environment control conditions based on theexecution time t for each combination of the environment controlconditions. The generated time division scheme for the environmentcontrol conditions will be described in detail later.

In Step S119, the environment control section 24 starts to executeenvironment control in accordance with the generated time divisionscheme and ends the execution of the program for the in-apparatusenvironment management process.

As such, in the exemplary embodiment, each of the environment controlconditions is changed based on the generated time division scheme duringimage formation. FIG. 7A illustrates the execution time, a rise in thetemperature of the developing rolls, and the degree of in-apparatuspollution for each combination of the environment control conditions asan example of the time division scheme. A rise in the temperature of thedeveloping rolls and the degree of in-apparatus pollution in FIG. 7Arepresent changes in the environment control conditions while eachcombination of the environment control conditions is applied and aremeasurement results obtained by performing the environment control basedon the time division scheme.

The time division scheme illustrated in FIG. 7A indicates that when acontrol that sets the state of the volume of air from the fan 48 to A3and the state of changing by the opening changing unit 50 to B3 isexecuted for 5.23 minutes, the temperature of the developing rolls isincreased by 2.62° C. and the degree of pollution (relative value) isincreased by 0.84. In addition, the time division scheme indicates thatwhen a control that sets the state of the volume of air from the fan 48to A3 and the state of changing by the opening changing unit 50 to B2 isexecuted for 4.24 minutes, the temperature of the developing rolls isincreased by 2.54° C. and the relative value of the degree of pollutionis increased by 0.64.

While the order of controls in the time division scheme illustrated inFIG. 7A is such that the total of the number of times the volume of airfrom the fan 48 is changed and the number of times the opening state ischanged is minimum, the order of controls is not limited thereto. Forexample, changing may be executed in an order in which the time requiredfor changing of the environment control conditions is minimum. That is,in a case of changing the opening state, the changing includes amechanical control such as moving the lid portion and requires largertime than changing of the volume of air from the fan 48. Consideringthis point, the order of controls may be such that, for example, thenumber of times the opening state is changed is minimized, asillustrated in FIG. 7B.

FIG. 8 illustrates a measurement result for a rise in the temperature ofthe developing rolls in a case of changing the environment controlconditions based on the time division scheme illustrated in FIG. 7A.FIG. 9 illustrates a measurement result for pollution in a case ofchanging the environment control conditions based on the exampleillustrated in FIG. 7A.

FIG. 8 illustrates a relationship a between an elapsed time and a risein the temperature of the developing rolls in a case of performing theenvironment control based on the time division scheme. In addition, FIG.8 illustrates a relationship b between the elapsed time and a rise inthe temperature of the developing rolls in a case where a combination ofthe environment control conditions in which the state of the volume ofair from the fan 48 is set to A2 and the state of changing by theopening changing unit 50 is set to B2 operates continuously for 30minutes as a standard operating state of the environment control. Inaddition, FIG. 8 illustrates a relationship c between the elapsed timeand a rise in the temperature of the developing rolls in a case ofprioritizing suppression of a rise in the temperature of the developingrolls, that is, in a case where a combination of the environment controlconditions in which the state of the volume of air from the fan 48 isset to A3 and the state of changing by the opening changing unit 50 isset to B1 operates continuously for 30 minutes. In addition, FIG. 8illustrates a relationship d between the elapsed time and a rise in thetemperature of the developing rolls in a case of prioritizingsuppression of pollution, that is, in a case where a combination of theenvironment control conditions in which the state of the volume of airfrom the fan 48 is set to A1 and the state of changing by the openingchanging unit 50 is set to B3 operates continuously for 30 minutes.

FIG. 9 illustrates a relationship e between the elapsed time and thedegree of pollution in a case of performing the environment controlbased on the time division scheme. In addition, FIG. 9 illustrates arelationship f between the elapsed time and the degree of pollution in acase where a combination of the environment control conditions in whichthe environment control conditions are fixed to predetermined standardvalues as a standard operating state operates continuously for 30minutes. In addition, FIG. 9 illustrates a relationship g between theelapsed time and the degree of pollution in a case where a combinationof the environment control conditions that prioritizes suppression of arise in the temperature of the developing rolls operates continuouslyfor 30 minutes. Similarly, FIG. 9 illustrates a relationship h betweenthe elapsed time and the degree of pollution in a case where acombination of the environment control conditions that prioritizessuppression of pollution operates continuously for 30 minutes.

As illustrated in FIG. 8 and FIG. 9, opposite results are obtained insuch a manner that the in-apparatus pollution is increased in a case ofprioritizing suppression of a rise in the temperature of the developingrolls (relationships c and g), while the temperature of the developingrolls is increased in a case of prioritizing suppression of pollution(relationships d and h). However, in the present exemplary embodiment(relationships a and e), it is understood that pollution is suppressedalong with suppression of a rise in the temperature of the developingrolls during image formation. As such, performing controls based on thetime division scheme generated in the present exemplary embodimentallows the in-apparatus environment control to be achieved according tothe target values of the environment state in a case of controlling theenvironment control conditions by changing the environment controlconditions to one of three-level discrete states.

When each of the environment control conditions of control targets ischanged, the value of each of the environment control conditions ofcontrol targets may be changed from a large value (HIGH) to a smallvalue (LOW) or from a small value (LOW) to a large value (HIGH). Thechanging may be executed in order from the largest execution time orfrom the minimum execution time. Alternatively, power consumptions in acase of performing the changing in each order may be calculated, and thechanging may be executed in the order in which the power consumption isminimum.

As such, in the present exemplary embodiment, the environment state in acase of executing image formation under the environment controlconditions including a predetermined volume of air, a predeterminedopening state, and a predetermined path is estimated based on the imageforming data for instructing execution of image formation. The timedivision scheme for the environment control during image formation isgenerated from calculation results in which the volume of air and theopening state that maintain the temperature of the developing rolls, thedegree of noise, and the degree of pollution less than or equal topredetermined target values are calculated from the estimatedenvironment state. The environment state is controlled based on thegenerated time division scheme.

Accordingly, stabilized image quality and stabilized operation aresecured in the image forming apparatus 10 according to the presentexemplary embodiment, and the in-apparatus environment is stabilized byusing an inexpensive control system without use of a high-accuracyin-apparatus environment management system.

The present exemplary embodiment is described in a case of using theimage forming data in calculation of the necessary time required forimage formation but is not limited thereto. For example, as the timerequired for image formation is increased, the temperature of thedeveloping rolls is increased, thereby producing a high possibility ofmalfunction. Considering this point, when the target values of theenvironment state are determined, the image forming conditions includedin the image forming data may be used for setting such that the targetvalue of the temperature of the developing rolls is decreased as thenecessary time is increased. Alternatively, the image forming conditionsincluded in the image forming data may be used for setting such that thetarget value of the temperature of the developing rolls is set to aminimum value if the necessary time is greater than or equal to apredetermined threshold.

The possibility that high image quality is required is increased as, forexample, the proportion of a color image in the formed image isincreased. Considering this point, when the target values of theenvironment state are determined, the image forming conditions includedin the image forming data may be used for setting such that the targetvalue of the degree of pollution is decreased as the proportion of acolor image in the formed image is increased. Alternatively, the targetvalue of the degree of pollution may be set to a minimum value if theproportion of a color image in the formed image is greater than or equalto a predetermined threshold.

The present exemplary embodiment is described in a case of setting thetarget values of the environment state in accordance with the estimationresult for the environment state but is not limited thereto. The targetvalues of the environment state may be set in advance to fixed values.

The present exemplary embodiment is described in a case where multipleopening portions are disposed in the casing of the image formingapparatus 10 but is not limited thereto. One opening portion may bedisposed in the casing of the image forming apparatus 10. In this case,the opening area of the opening portion may be changed by covering atleast a part of the opening portion with the lid portion.

The present exemplary embodiment is described in a case of using aBayesian network in estimation of the environment state and estimationof the environment control conditions, but the estimation method is notlimited thereto. A neural network, a model-based network, a rule-basednetwork, and the like may be used.

The present exemplary embodiment is described in a case of applying thein-apparatus environment management apparatus to the image formingapparatus 10 that includes the developing rolls. However, the target forapplication of the in-apparatus environment management apparatusaccording to the present exemplary embodiment is not limited to theimage forming apparatus 10. The in-apparatus environment managementapparatus is applied to electronic apparatuses such as a personalcomputer, a mobile terminal, and a smartphone. The in-apparatusenvironment management apparatus according to the present exemplaryembodiment is also applied to electrical appliances such as arefrigerator, a washing machine, a television, a video recording andreproducing machine, and a dryer.

The foregoing description of the exemplary embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Obviously, many modificationsand variations will be apparent to practitioners skilled in the art. Theembodiments were chosen and described in order to best explain theprinciples of the invention and its practical applications, therebyenabling others skilled in the art to understand the invention forvarious embodiments and with the various modifications as are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

What is claimed is:
 1. An environment management apparatus for inside ofa machine, the apparatus comprising: an estimator that estimates anenvironment state in the machine in a case of executing a process undera predetermined control condition, from process execution data forinstructing execution of the process; and a generator that generates,for the environment state estimated by the estimator, a time-seriesscheme for environment control during the execution of the process froma calculation result obtained by calculating a control condition whichmaintains the environment state to be less than or equal to apredetermined target value, wherein the generator is configured to setthe control condition which maintains the environment state to meettarget values for a volume of air from a fan, a target value for anopening state of at least one opening portion, and a defined path ofairflow, wherein the environment control comprises changing the volumeof air from the fan, changing the opening state of the at least oneopening portion by an opening changing unit, and changing the definedpath of airflow by a path changing unit in a time-series manner insynchronization with image formation executed by an image forming unitbased on the time-series scheme, and wherein the generator generates thetime-series scheme in such a manner that if mechanical changing isincluded in changing the control condition which maintains theenvironment state, a number of times the mechanical changing is executedis minimum when environment control is executed based on the time-seriesscheme.
 2. The environment management apparatus according to claim 1,wherein the estimator estimates the environment state using a Bayesiannetwork, and the generator generates, for the environment stateestimated by the estimator, the time-series scheme for the environmentcontrol during the process from the calculation result obtained bycalculating the control condition that maintains the environment stateto be less than or equal to the predetermined target value using theBayesian network.
 3. The environment management apparatus according toclaim 1, wherein the generator generates the time-series scheme in sucha manner that a time required for changing of the control conditionwhich maintains the environment state is minimum when environmentcontrol is executed based on the scheme.
 4. The environment managementapparatus according to claim 1, wherein the generator generates thetime-series scheme in such a manner that power required for changing ofthe control condition which maintains the environment state is minimumwhen environment control is executed based on the time-series scheme. 5.An electronic machine comprising: the environment management apparatusaccording to claim 1; and a controller that controls an environment inthe electronic machine based on the time-series scheme generated by thegenerator.
 6. The electronic machine according to claim 5, furthercomprising: a fan that blows air in the electronic machine, wherein thecontroller controls the fan based on the time-series scheme to change avolume of air.
 7. The electronic machine according to claim 5, furthercomprising: at least one opening portion that is provided so as topenetrate a casing of the electronic machine; and the opening changingunit that changes the opening state of the at least one opening portion,wherein the controller controls the opening changing unit based on thetime-series scheme to change an opening area of the at least one openingportion.
 8. The electronic machine according to claim 5, furthercomprising: a plurality of paths of airflow; and a path changing unitthat changes the path along which air flows, wherein the controllercontrols the path changing unit based on the time-series scheme tochange the path along which air flows to one of the plurality of pathsof airflow.
 9. An image forming apparatus comprising: an estimator thatestimates at least two of a temperature of a developing roll, a degreeof noise, and a degree of pollution which correspond to an environmentstate in the image forming apparatus in a case of executing imageformation under at least two of control conditions including apredetermined volume of air, a predetermined opening state, and apredetermined path along which air flows, from image forming data forinstructing execution of the image formation; a generator thatgenerates, for the environment state estimated by the estimator, atime-series scheme for environment control during the execution of theimage formation from a calculation result obtained by calculating atleast two of a volume of air, an opening state, and a path whichmaintain at least two of the temperature of the developing roll, thedegree of noise, and the degree of pollution to be less than or equal topredetermined target values; and a controller that controls anenvironment state in the image forming apparatus based on thetime-series scheme generated by the generator.
 10. The image formingapparatus according to claim 9, wherein the generator generates, for theenvironment state estimated by the estimator, the scheme by normalizing,by necessary time required for image formation, probability valuescalculated using a Bayesian network that the at least two of the volumeof air, the opening state, and the path which maintain the at least twoof the temperature of the developing roll, the degree of noise, and thedegree of pollution to be less than or equal to the predetermined targetvalues.
 11. The image forming apparatus according to claim 10, whereinthe estimator obtains at least one of a temperature in the image formingapparatus and a humidity in the image forming apparatus and estimatesthe environment state by using the at least one of the temperature andthe humidity.
 12. The image forming apparatus according to claim 10,wherein the generator generates the scheme in such a manner that anumber of times the opening state is changed is minimum.
 13. The imageforming apparatus according to claim 9, wherein the estimator obtains atleast one of a temperature in the image forming apparatus and a humidityin the image forming apparatus and estimates the environment state usingthe at least one of the temperature and the humidity.
 14. The imageforming apparatus according to claim 13, wherein the generator generatesthe scheme in such a manner that a number of times the opening state ischanged is minimum.
 15. The image forming apparatus according to claim9, wherein the generator generates the scheme in such a manner that anumber of times the opening state is changed is minimum.
 16. The imageforming apparatus according to claim 9, wherein the predetermined targetvalues are set based on an image forming condition included in the imageforming data.
 17. The image forming apparatus according to claim 16,wherein the predetermined target values are set based on necessary timerequired for image formation that is calculated based on the imageforming condition included in the image forming data.
 18. An environmentmanagement method for inside of a machine, the method comprising:estimating an environment state in the machine in a case of executing aprocess under a predetermined control condition, from process executiondata for instructing execution of the process; and generating, for theestimated environment state, a time-series scheme for environmentcontrol during the execution of the process from a calculation resultobtained by calculating a control condition which maintains theenvironment state to be less than or equal to a predetermined targetvalue, and setting the control condition which maintains the environmentstate to meet target values for a volume of air from a fan, a targetvalue for an opening state of at least one opening portion, and adefined path of airflow, wherein the control condition which maintainsthe environment state comprises changing the volume of air from the fan,changing the opening state of the at least one opening portion by anopening changing unit, and changing the defined path of airflow by apath changing unit in a time-series manner in synchronization with imageformation executed by an image forming unit based on the time-seriesscheme, and wherein the time-series scheme is generated in such a mannerthat if mechanical changing is included in the changing process of thecontrol condition which maintains the environment state, a number oftimes the mechanical changing is executed is minimum when environmentcontrol is executed based on the time-series scheme.